The Bragg coherent diffraction imaging technique performed using Advanced Photon Source instruments provides scientists with the unique ability to determine structure and strain formation on materials at the nanometer scale. This technique has emerged as a powerful technique to study materials under operando and in-situ conditions, including line defect dynamics in battery nanoparticles during charge cycling, phonon transport, and mechanically induced defects in polycrystalline materials.The iterative algorithms traditionally used to recover a material’s strain and stress information struggle to converge and are computationally expensive. To address these algorithmic shortcomings that limit scope and speed Argonne researchers have built and trained a deep convolutional encoder-decoder network that maps between raw diffraction data and corresponding object structure and strain. This technique is ~500 times faster than traditional algorithms, while also being more robust to the presence of large strains in materials.